Although research in natural language generation has led to the development of numerous methods and reusable software tools, we feel that building comparably simple application systems still involves more hand-crafted skills than systematic methodology. In our view, this is due to the fact that most available tools are oriented towards contributing to a general purpose generation system rather than supporting the economic development of dedicated applications. In order to improve this situation, we present a methodology for developing application-oriented report generation with limited effort, emphasizing domain- and user-specific preferences over general-purpose communicative principles. Key parts in our approach comprise building an ontologically minimal initial representation on the basis of user parameters and associated domain data, the successive refinement of this initial representation by making implicit information explicit enough for fleshing out selected text and sentence patterns, and the opportunistic combination of linguistically motivated methods with template-based generation. This methodology should enable system developers to build application-oriented report generators more systematically and with reduced effort.